Falling is a significant problem in the care of the elderly that can lead to morbidity and mortality. From a physical perspective, falls cause injuries, while from the mental perspective, falls cause fear-of-falling, which in turn leads to social isolation and depression.
Fall detection systems are being developed which can provide an automated and reliable means for detecting when a user has fallen. If a fall is detected, the system issues an alarm which summons help to the user. This assures the user that adequate measures will be taken in the event that a fall occurs.
Commonly, automated fall detection systems are based on an accelerometer that is to be attached to the user's body. The fall detection system tracks the signals from the accelerometer and determines that a fall has taken place if a characteristic pattern is identified. A typical pattern is a combination of a high impact value in which the acceleration signal exceeds a preconfigured threshold, followed by a period of relative or actual inactivity characterised by relatively constant acceleration, for example gravity only (or no acceleration depending on the type of accelerometer used), since the user is lying motionless on the ground. The pattern may continue by revealing activity, deviating from the relatively constant period of acceleration, when the user stands up again.
Some fall detection systems can determine an inability of the user to get up after a fall (as represented by an extended period of inactivity), and use this determination to trigger or issue an alarm signal. One such system is described in WO 2005/016143.